Scholarly Publications - BCBI
Permanent URI for this collectionhttps://hdl.handle.net/11693/115591
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Browsing Scholarly Publications - BCBI by Author "Babur, Özgün"
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Item Open Access Algorithms for effective querying of compound graph-based pathway databases(BioMed Central Ltd., 2009-11-16) Doğrusöz, Uğur; Çetintaş, Ahmet; Demir, Emek; Babur, ÖzgünBackground: Graph-based pathway ontologies and databases are widely used to represent data about cellular processes. This representation makes it possible to programmatically integrate cellular networks and to investigate them using the well-understood concepts of graph theory in order to predict their structural and dynamic properties. An extension of this graph representation, namely hierarchically structured or compound graphs, in which a member of a biological network may recursively contain a sub-network of a somehow logically similar group of biological objects, provides many additional benefits for analysis of biological pathways, including reduction of complexity by decomposition into distinct components or modules. In this regard, it is essential to effectively query such integrated large compound networks to extract the sub-networks of interest with the help of efficient algorithms and software tools. Results: Towards this goal, we developed a querying framework, along with a number of graph-theoretic algorithms from simple neighborhood queries to shortest paths to feedback loops, that is applicable to all sorts of graph-based pathway databases, from PPIs (protein-protein interactions) to metabolic and signaling pathways. The framework is unique in that it can account for compound or nested structures and ubiquitous entities present in the pathway data. In addition, the queries may be related to each other through "AND" and "OR" operators, and can be recursively organized into a tree, in which the result of one query might be a source and/or target for another, to form more complex queries. The algorithms were implemented within the querying component of a new version of the software tool PATIKAweb (Pathway Analysis Tool for Integration and Knowledge Acquisition) and have proven useful for answering a number of biologically significant questions for large graph-based pathway databases. Conclusion: The PATIKA Project Web site is http://www.patika.org. PATIKAweb version 2.1 is available at http://web.patika.org. © 2009 Dogrusoz et al; licensee BioMed Central Ltd.Item Open Access The BioPAX community standard for pathway data sharing(Nature Publishing Group, 2010-09) Demir, Emek; Cary, M. P.; Paley, S.; Fukuda, K.; Lemer, C.; Vastrik, I.; Wu, G.; D'Eustachio, P.; Schaefer, C.; Luciano, J.; Schacherer, F.; Martinez-Flores, I.; Hu, Z.; Jimenez-Jacinto, V.; Joshi-Tope, G.; Kandasamy, K.; Lopez-Fuentes, A. C.; Mi, H.; Pichler, E.; Rodchenkov, I.; Splendiani, A.; Tkachev, S.; Zucker, J.; Gopinath, G.; Rajasimha, H.; Ramakrishnan, R.; Shah, I.; Syed, M.; Anwar, N.; Babur, Özgün; Blinov, M.; Brauner, E.; Corwin, D.; Donaldson, S.; Gibbons, F.; Goldberg, R.; Hornbeck, P.; Luna, A.; Murray-Rust, P.; Neumann, E.; Reubenacker, O.; Samwald, M.; Iersel, Martijn van; Wimalaratne, S.; Allen, K.; Braun, B.; Whirl-Carrillo, M.; Cheung, Kei-Hoi; Dahlquist, K.; Finney, A.; Gillespie, M.; Glass, E.; Gong, L.; Haw, R.; Honig, M.; Hubaut, O.; Kane, D.; Krupa, S.; Kutmon, M.; Leonard, J.; Marks, D.; Merberg, D.; Petri, V.; Pico, A.; Ravenscroft, D.; Ren, L.; Shah, N.; Sunshine, M.; Tang R.; Whaley, R.; Letovksy, S.; Buetow, K. H.; Rzhetsky, A.; Schachter, V.; Sobral, B. S.; Doğrusöz, Uğur; McWeeney, S.; Aladjem, M.; Birney, E.; Collado-Vides, J.; Goto, S.; Hucka, M.; Novère, Nicolas Le; Maltsev, N.; Pandey, A.; Thomas, P.; Wingender, E.; Karp, P. D.; Sander, C.; Bader, G. D.Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery. © 2010 Nature America, Inc. All rights reserved.Item Open Access ChiBE: interactive visualization and manipulation of BioPAX pathway models(Oxford University Press, 2010-02-01) Babur, Özgün; Doğrusöz, Uğur; Demir, Emek; Sander, C.SUMMARY: Representing models of cellular processes or pathways in a graphically rich form facilitates interpretation of biological observations and generation of new hypotheses. Solving biological problems using large pathway datasets requires software that can combine data mapping, querying and visualization as well as providing access to diverse data resources on the Internet. ChiBE is an open source software application that features user-friendly multi-view display, navigation and manipulation of pathway models in BioPAX format. Pathway views are rendered in a feature-rich format, and may be laid out and edited with state-of-the-art visualization methods, including compound or nested structures for visualizing cellular compartments and molecular complexes. Users can easily query and visualize pathways through an integrated Pathway Commons query tool and analyze molecular profiles in pathway context. AVAILABILITY: http://www.bilkent.edu.tr/%7Ebcbi/chibe.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.Item Open Access Discovering modulators of gene expression(Oxford University Press, 2010-09-01) Babur, Özgün; Demir, Emek; Gönen, M.; Sander, C.; Doğrusöz, UğurProteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein-protein interactions and transcription factor-target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes. © The Author(s) 2010. Published by Oxford University Press.Item Open Access Microarray data analysis and pathway activity inference in PATIKA(ISCB Org, 2004) Babur, Özgün; Demir, Emek; Ayaz, Aslı; Doğrusöz, Uğur; Sakarya, OnurPathway activity inference attempts to infer differential activity of cellular networks, given a qualitative state - transition model of the network and an expression profile of RNA molecules. We present an efficient algorithm for this problem, implemented as part of microarray data analysis component of PATIKA, a pathway analysis tool.Item Open Access An ontology for collaborative construction and analysis of cellular pathways(Oxford University Press, 2004-02-12) Demir, Emek; Babur, Özgün; Doğrusöz, Uğur; Gürsoy, Atilla; Ayaz, Aslı; Güleşır, Gürcan; Nişancı, Gürkan; Çetin Atalay, RengülMotivation: As the scientific curiosity in genome studies shifts toward identification of functions of the genomes in large scale, data produced about cellular processes at molecular level has been accumulating with an accelerating rate. In this regard, it is essential to be able to store, integrate, access and analyze this data effectively with the help of software tools. Clearly this requires a strong ontology that is intuitive, comprehensive and uncomplicated. Results: We define an ontology for an intuitive, comprehensive and uncomplicated representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information via collaboration, and supports manipulation of the stored data. In addition, it facilitates concurrent modifications to the data while maintaining its validity and consistency. Furthermore, novel structures for representation of multiple levels of abstraction for pathways and homologies is provided. Lastly, our ontology supports efficient querying of large amounts of data. We have also developed a software tool named pathway analysis tool for integration and knowledge acquisition (PATIKA) providing an integrated, multi-user environment for visualizing and manipulating network of cellular events. PATIKA implements the basics of our ontology. © Oxford University Press 2004; All rights reserved.Item Open Access Pathway activity inference using microarray data(Bilkent Center for Bioinformatics (BCBI), 2004) Babur, Özgün; Demir, Emek; Ayaz, Aslı; Doğrusöz, Uğur; Sakarya, OnurMotivation: Microarray technology provides cell-scale expression data; however, analyzing this data is notoriously difficult. It is becoming clear that system-oriented methods are needed in order to best interpret this data. Combining microarray expression data with previously built pathway models may provide useful insight about the cellular machinery and reveal mechanisms that govern diseases. Given a qualitative state - transition model of the cellular network and an expression profile of RNA molecules, we would like to infer possible differential activity of the other molecules such as proteins on this network. Results: In this paper an efficient algorithm using a new approach is proposed to attack this problem. Using the regulation relations on the network, we determine possible scenarios that might lead to the expression profile, and qualitatively infer the activity differences of the molecules between test and control samples. Availability: This new analysis method has been implemented as part of a microarray data analysis component within PATIKA (Pathway Analysis Tool for Integration and Knowledge Acquisition), which is a software environment for pathway storage, integration and analysis. Facilities for easy analysis and visualization of the results is also provided. Contact: http://www.patika.org.Item Open Access PATIKA: An informatics infrastructure for cellular networks(ISCB Org, 2004) Aksay, Çağrı; Ayaz, Aslı; Babur, Özgün; Bilgin, C.; Çetintaş, Ahmet; Çivril, Ali; Çolak, Recep; Çözen, G.; Demir, Emek; Doğrusöz, Uğur; Erson, Zeynep; Gerdaneri, Ozan; Giral, Erhan; Güleşır, Gürcan; Nişancı, Gürkan; Sakarya, O.; Yıldırım, HilmiThe PATIKA Project aims for an informatics infrastructure to cope with the inherently complex cellular pathway data and provides software tools with sophisticated visualization technology around a central database using an extensive ontology and data integration mechanisms. It also features advanced database querying, microarray data analysis, and automatic layout components.Item Open Access PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways(Oxford University Press, 2002-06) Demir, Emek; Babur, Özgün; Doğrusöz, Uğur; Gürsoy, Atilla; Nişancı, Gürkan; Çetin Atalay, Rengül; Öztürk, MehmetMotivation: Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. Results: We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named PATIKA (Pathway Analysis Tool for Integration and Knowledge Acquisition). PATIKA is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that PATIKA will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development.Item Open Access PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways(American Society for Biochemistry and Molecular Biology(ASBMB), 2002-09) Demir, Emek; Babur, Özgün; Doğrusöz, Uğur; Gürsoy, Atilla; Nişancı, Gürkan; Çetin Atalay, Rengül; Öztürk, MehmetItem Open Access PATIKAmad: putting microarray data into pathway context(Wiley - V C H Verlag GmbH & Co. KGaA, 2008-06) Babur, Özgün; Colak, Recep; Demir, Emek; Doğrusöz, UğurHigh-throughput experiments, most significantly DNA microarrays, provide us with system-scale profiles. Connecting these data with existing biological networks poses a formidable challenge to uncover facts about a cell's proteome. Studies and tools with this purpose are limited to networks with simple structure, such as protein-protein interaction graphs, or do not go much beyond than simply displaying values on the network. We have built a microarray data analysis tool, named PATIKAmad, which can be used to associate microarray data with the pathway models in mechanistic detail, and provides facilities for visualization, clustering, querying, and navigation of biological graphs related with loaded microarray experiments. PATIKAmad is freely available to noncommercial users as a new module of PATIKAweb at http://web.patika.org. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA.Item Open Access PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization(Oxford University Press, 2006-02-01) Doğrusöz, Uğur; Erson, E. Zeynep; Giral, Erhan; Demir, Emek; Babur, Özgün; Çetintaş, Ahmet; Çolak, RecepSummary: PATIKAweb provides a Web interface for retrieving and analyzing biological pathways in the PATIKA database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats. © The Author 2005. Published by Oxford University Press. All rights reserved.Item Open Access PATIKAweb: a Web service for querying, visualizing and analyzing a graph-based pathway database(ISCB Org, 2005-06) Aksay, Çağrı; Arık, Fatma; Ataer, Esra; Ayaz, Aslı; Babur, Özgün; Belviranlı, Mehmet E.; Çetintaş, Ahmet; Çolak, Recep; Çözen, G.; Demir, Emek; Dilek, Alptuğ; Doğrusöz, Uğur; Giral, Erhan; Kaya, Engin; Küçük, Evren; Tekin, A. S.; Yıldırım, Hilmi; Erson, ZeynepPATIKAweb provides a Web service for retrieving and analyzing biological pathways in PATIKA database, which currently contains data integrated from popular public pathway databases like Reactome. It features a user-friendly interface, dynamic visualization, advanced graph-theoretic queries for extracting biologically important phenomena and exporting facilities to various exchange formats.